Exposure to environmental chemicals among Korean adults-updates from the second Korean National Environmental Health Survey (2012–2014)
Bibliographic record
Abstract
National biomonitoring program can offer solid scientific evidence on exposure profiles of environmental chemicals at a national level, and provide a snapshot of changing exposure level over time. Therefore, several countries have maintained such programs for developing environmental health policies. The Korean National Environmental Health Survey (KoNEHS) was designed to understand the level of human exposure to environmental chemicals by time and location, and to identify possible sources of such exposure. The 2nd stage of KoNEHS, which was conducted between 2012 and 2014, examined a total of 6478 adult subjects over 19 years of age, and measured 21 environmental chemicals of major policy concern. Compared to the findings from the first stage monitoring (2009-2011), slightly higher levels of blood lead were observed, while those of mercury remained similar. Blood metal concentrations, however, were higher than those reported from national biomonitoring programs of United States, Germany and Canada. The urinary concentrations of phthalates metabolites were lower, but those of t,t-muconic acid and BPA were higher than those reported in the first stage survey. The urinary cotinine level decreased perhaps reflecting general declining patterns of first- and second-hand smoking. The results of the second stage survey were made available for public use since April 2016. Some policy efforts appear to be at least in part effective on mitigating chemical exposure among people, e.g., urinary phthalate metabolites and cotinine, while further confirmations are warranted. In-depth assessments will be conducted to identify vulnerable groups and important exposure pathways.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".